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Writers Cramp for Mouse Bioinformaticists

The publication of the mouse genome sequence in Nature was just one paper in a flurry of related bioinformatics research published in several scientific journals last week.

Nature also offered a detailed SNP analysis of the mouse genome, performed by Claire Wade and colleagues at the Whitehead Institute. The Whitehead researchers aligned the recently assembled genome sequence of the Black 6 strain with available sequences from a second, strain 129, and analyzed rates of variation between the two. They found that only one third of the genome in any comparison falls into long regions of high SNP rate, with the remaining two-thirds having very little or no variation.

Genome Research published a paper by UCSD’s Pavel Pevzner and Glenn Tesler on a new algorithm called GRIMM-Synteny that differentiates between micro-level genome rearrangements (intrachromosomal rearrangements with a span below 1 Mb) and macro-level rearrangements (intrachromosomal rearrangements with a span above 1 Mb as well as interchromosomal rearrangements).

Current rearrangement algorithms don’t distinguish between these two types of rearrangements, according to the authors, and “since some micro-rearrangements may be caused by fragment assembly errors, mixing micro- and macro-rearrangements within one rearrangement scenario may produce a distorted picture greatly influenced by the sequencing errors in draft genomic sequences.”

The algorithm is based on the GRIMM (Genome Rearrangements in Man and Mouse) software developed by Tesler earlier this year.

Application of the software to the mouse sequence indicated that over 245 major rearrangements represent “dramatic evolutionary events.” Many of those segments reveal multiple micro-rearrangements, at least 3,170 within these major blocks — “a much higher figure than previously thought,” according to Tesler.

Genome Biology has its own mouse bioinformatics paper to offer as well, an article by Michael Zhang and colleagues at Cold Spring Harbor Laboratory that describes a three-way comparison between the publicly available mouse sequence, the human genome sequence, and Celera’s mouse sequence.

Zhang gave the Celera assembly the thumbs up for “higher accuracy in base pairs and overall higher coverage of the genome,” while noting that the public mouse assembly “has higher sequence quality in some newly finished BAC regions.”

The team identified over 6,000 potentially novel genes by analyzing the similarities between the different genome sequences, bringing their estimate of the number of protein-coding genes in human to 37,000.

 

ISCB Board Condemns Shutdown of PubScience

In an e-mail to ISCB members last week, Phil Bourne, president of the International Society for Computational Biology, said the ISCB board of directors has drafted a letter to the journals Science and Nature regarding the proposed closure of the DOE’s PubScience web site for journal articles.

Bourne circulated a copy of the brief statement, which notes that “free access to publicly funded databases such as PubScience, PubMed, Medline and GenBank reflects the public’s role in funding the science that led to these data and provides a cost-effective means for disseminating this information to the scientific community."

Bourne encouraged any members who have concerns about the statement to contact [email protected] The board plans to send the letter to both journals on December 13, 2002.

 

Gene-IT Says Blast, Fasta Ineffective for IP Searches

Gene-IT’s sequence comparison algorithm works better than public search tools to determine whether a novel gene has already been discovered and patented, according to a study in the December issue of Nature Biotechnology.

Intellectual property searches on DNA or protein sequences can be a tricky matter, noted the authors, a group of bioinformatics and legal experts from Pfizer and Gene-IT. Most search algorithms are designed to look for biological similarity, and are tuned for different parameters than the requirements set down by intellectual property law.

Blast and Fasta, for example, are homology-based, and determine the similarity between genes based on parameters set by the searcher. This flexibility means that two gene similarity searches may deliver different answers. A quirk of patent law further complicates the process: Patents are usually granted not just for the sequence itself but for all those closely related to it.

Gene-IT’s GenePAST algorithm uses a different strategy to identify similarities. With pairwise alignment, the algorithm identifies sequences that may be similar but of different lengths, as may be the case with splice variants.

This approach is not useful for research, the authors write, since it does not take into account phylogenetic relationships. But because it mirrors intellectual property law, it can be useful for establishing the patent status of a gene.

Gene-IT offers a patent investigation service that uses this algorithm.

 

Entelos Extends Organon Collaboration

Entelos said last week that it would expand its existing research collaboration with Organon in the area of rheumatoid arthritis. The companies first entered the collaboration in May 2001.

Under the terms of the expanded agreement, Organon will provide up-front fees, milestone payments, and royalties on the sale of immunological and inflammatory drugs resulting from the collaboration. Organon will also participate in and provide funding for the development of the next generation of Entelos’ RA PhysioLab technology, a dynamic, large-scale mathematical model of a prototypical rheumatoid arthritis joint that can rapidly simulate experiments and clinical trials related to human rheumatoid arthritis.

Financial details of the deal were not disclosed.

“The first generation of the RA PhysioLab technology developed during our collaboration is now being implemented in our research efforts. In potential, this technology can reveal important insights into the pathophysiology of RA and the subtle balances that are achieved by various cytokines in different phenotypes of the condition,” said Jan Meijerink, vice president of Organon’s cardiovascular and immunology program, in a statement.

Filed under

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